ArticleFrontiers in plant science2015
Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping.
Article in Frontiers in plant science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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Who cites it
88 citing papers in PubMed.
- Scaling law links plant growth variation to grain yield in wheat stands.The New phytologist · 2026Article
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- Integrative GWAS and transcriptomic analyses identify candidate genes associated with oil content and fatty acid composition in safflower.BMC plant biology · 2026Article
- Genome-wide association analysis of fiber-related traits and identification of diagnostic SNP markers differentiating spelt wheat (Frontiers in plant science · 2026Article
- Genome-wide association analysis identifies SNP loci for multi-stage yield-related traits in wheat.Frontiers in plant science · 2026Article
- MAGIC population-based genetic dissection of yield-related traits under heat stress in wheat (Frontiers in plant science · 2026Article
- Population genomics uncovers loci for trait improvement in the indigenous African cereal tef (Eragrostis tef).Communications biology · 2025Article
- Article
- Identification and validation of two quantitative trait loci showing pleiotropic effect on multiple grain-related traits in bread wheat (Triticum aestivum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Pleiotropic Quantitative Trait Loci (QTL) Mining for Regulating Wheat Processing Quality- and Yield-Related Traits.Plants (Basel, Switzerland) · 2024Article
- Fungal Disease Tolerance with a Focus on Wheat: A Review.Journal of fungi (Basel, Switzerland) · 2024Review
- Mining of QTLs for Spring Bread Wheat Spike Productivity by Comparing Spring Wheat Cultivars Released in Different Decades of the Last Century.Plants (Basel, Switzerland) · 2024Article
- Molecular Markers Help with Breeding for Agronomic Traits of Spring Wheat in Kazakhstan and Siberia.Genes · 2024Article
- Meta-QTL mapping for wheat thousand kernel weight.Frontiers in plant science · 2024Article
- Genetic Dissection of Seasonal Changes in a Greening Plant Based on Time-Series Multispectral Imaging.Plants (Basel, Switzerland) · 2023Article
- Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency.Plants (Basel, Switzerland) · 2023Review
- Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat.The plant genome · 2023Article
- Genome-wide association study of lipase and esterase in wholegrain wheat flour (Triticum aestivum L.).PloS one · 2023Article
- Identification of major QTLs for yield-related traits with improved genetic map in wheat.Frontiers in plant science · 2023Article
- A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800.Plants (Basel, Switzerland) · 2022Article
28 more citing papers are in PubMed but not listed here.
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15 authors.
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Abstract
Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.
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